2021 Volume 77 Issue 1 Pages 14-27
This paper, analyzed the residents’ emotions towards “transportation services” after great disaster by using Social Networking Services (SNS) in the case of a disaster that requires immediate implementations of transportation policies. Specifically, this research applied natural language processing to quantitatively analyze tweets related to public transportation in Hiroshima Prefecture, where the transportation infrastructure was damaged during the torrential rainstorm in July 2018, with the aim of getting feedback on transportation policies at the time of the disaster by estimating emotions. After qualitative analysis of tweets, this research assigned emotion polarity values to verbs and adjectives based on the emotion theory model proposed by Plutchik (1980). The emotion polarity values for each phase were then calculated and evaluated. As a result, the emotions of SNS users were found to have changed as the transportation network shifted. The results indicate that obtained from SNS is a useful reference for the management of transportation policies regarding transportation problems during disasters.
